progress 0.0.4

lib/pt_strategy/live/live_strategy.py

@@ -42,14 +42,14 @@ class PtLiveStrategy(NamedObject):
     # for presentation: history of prediction values and trading signals
     predictions_df_: pd.DataFrame
     trading_signals_df_: pd.DataFrame
+    allowed_md_lag_sec_: int
+
 
     def __init__(
         self,
         config: Config,
         pairs_trader: PairTrader,
     ):
-        # import copy
-        # self.config_ = Config(json_src=copy.deepcopy(config.data()))
         self.config_ = config
 
         self.pairs_trader_ = pairs_trader
@@ -83,6 +83,8 @@ class PtLiveStrategy(NamedObject):
         )
         assert self.history_depth_sec_ > 0, "history_depth_hours cannot be 0"
 
+        self.allowed_md_lag_sec_ = self.config_.get_value("allowed_md_lag_sec", 3)
+
         await self.pairs_trader_.subscribe_md()
 
         self.open_threshold_ = self.config_.get_value(
@@ -136,23 +138,29 @@ class PtLiveStrategy(NamedObject):
             Log.warning(f"{self.fname()} list of aggregates IS EMPTY")
             return False
 
-        ALLOWED_LAG_SEC = 5.0
         curr_ns = current_nanoseconds()
-        LAG_THRESHOLD = NanosT((self.interval_sec() + ALLOWED_LAG_SEC) * NanoPerSec)
         
         # MAYBE check market data length
-        lag_ns = curr_ns - hist_aggr[-1].aggr_time_ns_
-        if lag_ns > LAG_THRESHOLD:
+        
+        # at 18:05:01 we should see data for 18:04:00
+        lag_sec = (curr_ns - hist_aggr[-1].aggr_time_ns_) / NanoPerSec - self.interval_sec()
+        if lag_sec > self.allowed_md_lag_sec_:
             Log.warning(
                 f"{self.fname()} {hist_aggr[-1].exch_inst_.details_short()}"
-                f" Lagging {int(lag_ns/NanoPerSec)} seconds:"
+                f" Lagging {int(lag_sec)} > {self.allowed_md_lag_sec_} seconds:"
                 f"\n{len(hist_aggr)} records"
                 f"\n{hist_aggr[-1].exch_inst_.base_asset_id_}: {hist_aggr[-1].tstamp()}"
                 f"\n{hist_aggr[-2].exch_inst_.base_asset_id_}: {hist_aggr[-2].tstamp()}"
-                # f" {hist_aggr[-1].exch_inst_.base_asset_id_}: {format_nanos_utc(hist_aggr[-1].aggr_time_ns_)}"
-                # f" {hist_aggr[-2].exch_inst_.base_asset_id_}: {format_nanos_utc(hist_aggr[-2].aggr_time_ns_)}"
             )
             return False
+        else:
+            Log.info(
+                f"{self.fname()} {hist_aggr[-1].exch_inst_.details_short()}"
+                f" Lag {int(lag_sec)} <= {self.allowed_md_lag_sec_} seconds"
+                f"\n{len(hist_aggr)} records"
+                f"\n{hist_aggr[-1].exch_inst_.base_asset_id_}: {hist_aggr[-1].tstamp()}"
+                f"\n{hist_aggr[-2].exch_inst_.base_asset_id_}: {hist_aggr[-2].tstamp()}"
+            )
         return True
 
     def _create_md_df(self, hist_aggr: List[MdTradesAggregate]) -> pd.DataFrame: